Some currently available data collection devices, such as hand-held image readers, are capable of capturing signatures as well as reading barcodes. The reading and decoding of a barcode represents an operation distinct from that involved in capturing a signature. The reading and decoding of a bar code involves the imaging and then decoding of a one or two dimensional graphic symbol into the alphanumeric sequence encoded by the symbol. The capturing of a signature involves identifying a region of interest and then storing an electronic visual copy/representation of the identified region of interest.
One approach to enabling the operation of an image reader as a barcode decoder and a signature capture device involves the input of a human operator. According to this approach, the human operator manually switches the mode of operation of the image reader between barcode decoding and signature capturing. One disadvantage of this approach is that the manual selection process requires additional training for personnel. This additional training is in contradiction with the ideal that the operational details of an image reader should be abstracted as much as possible. For example, the human operator should be able to employ the image reader by simply pointing the device and pulling an activation trigger. Another disadvantage is that the manual selection process can be time consuming. In the field of data collection, a premium is placed on efficient quick operation and even slight delays can be significant. The significance of these delays is compounded by the large number of times the barcode read or signature capture operation is activated in an image reader during a typical session.
Another approach to enabling the operation of an image reader as a barcode decoder and a signature capture device involves using a dataform decode operation to identify and locate the signature capture area. The dataform approach suffers from several drawbacks. One drawback is that if the dataform, such as a linear barcode or two dimensional symbology, has been damaged due to handling or defected through printing, the dataform decode failure will render the signature capture inoperable. Another drawback of the dataform approach is that space constraints can make it difficult to accommodate the space required for a dataform. For example on some shipping labels and on some driver's licenses, little free space is available for additional graphic elements. A further drawback of the dataform approach is that its operation is unintuitive. Although the human operator desires to capture the signature, he or she must aim the reader at the dataform instead of the signature. The result of this unintuitive approach is that frequently the signature image will be clipped due to improper orientation of the image reader. To achieve more acceptable operation, additional human operator training and feedback, with its commensurate costs and burdens, is often required.
Hence, there is a need for an image reader that facilitates the capturing of signatures while maintaining the image reader's ease of operation as a bar code reader.